Definition
The term Active Learning is generally used to refer to a learning problem or system where the learner has some role in determining on what data it will be trained. This is in contrast to Passive Learning, where the learner is simply presented with a training set over which it has no control. Active learning is often used in settings where obtaining labeled data is expensive or time-consuming; by sequentially identifying which examples are most likely to be useful, an active learner can sometimes achieve good performance, using far less training data than would otherwise be required.
Structure of Learning System
In many machine learning problems, the training data are treated as a fixed and given part of the problem definition. In practice, however, the training data are often not fixed beforehand. Rather, the learner has an opportunity to play a role in deciding what data will be acquired for training. This process is usually referred to as “active learning,” recognizing...
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Cohn, D. (2017). Active Learning. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning and Data Mining. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7687-1_916
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